Establishment Of A Risk Prediction Model For Intraoperative Hypothermia In Patients Undergoing Thoracoscopic Surgery

ObjectiveUsing cross-sectional analysis,study the risk factors of hypothermia during thoracoscopic surgery in patients.Construct a risk prediction model for intraoperative hypothermia in patients undergoing thoracoscopic surgery and verify the model for intraoperative hypothermia risk prediction in patients undergoing thoracoscopic surgery.MethodBased on the analysis method of cross-sectional survey,the information data of patients undergoing thoracoscopic surgery in a tertiary hospital from August 2021 to February 2023 were collected,and they were divided into non-hypothermic group and hypothermia group with reference to whether hypothermia was generated,and the logistic regression analysis method was used to effectively screen and determine the independent risk factors for intraoperative hypothermia,and at the same time,a predictive model was constructed and presented in the form of a nomogram.The Hosmer-Lemeshow,H-L,goodness-of-fit test method and the Receiver Operating Characteristic Curve(ROC)corresponding to the differentiation and calibration degree were used,and the calibration work was completed based on Bootstrap resampling 1000 times.The clinical utility of the model was evaluated by doing a decision curve analysis(DCA).Result1.A total of 193 study subjects were included in this study.According to whether patients experienced hypothermia during surgery,there were a total of 74 patients in the non hypothermia group,119 patients in the hypothermia group,and the incidence of intraoperative hypothermia in patients undergoing thoracoscopic surgery was approximately 61.66%.The results of logistic regression analysis showed that age(OR=1.069),infusion volume(OR=1.001),entry temperature(OR=0.209),active heating(OR=0.245),surgical duration(OR=5.903),and anesthesia opening time(OR=12.106)can be considered as independent risk factors for developing hypothermia in patients.2.The area under the curve(AUC)of the ROC curve of the hypothermia risk prediction model constructed this time is 0.95(95% CI: 0.92,0.98),in the ROC data curve results,the peak value of the Jordon index is 0.779,the corresponding optimal cut-off value is 0.265,the sensitivity parameter value is 94.1%,and the specificity parameter value is 83.8%;The chi-square value of the H-L goodness-of-fit test was 4.13,P=0.667,and the consistency coefficient value calculated after 1000 Bootstrap resampling was 0.947,and the DCA curve showed that using the nomogram model to predict intraoperative hypothermia in thoracoscopic surgery patients had a greater net benefit than the "all intervention" or "no intervention" strategy.ConclusionThe risk of intraoperative hypothermia in patients undergoing thoracoscopic surgery is relatively high.Patients with older age,large intraoperative infusion volume,longer surgical time,and a larger preparation time span for anesthesia and surgery can all be classified as risk factors for hypothermia.However,in the standard reference value range,higher entry temperature and active heating measures are protective factors for patients with intraoperative hypothermia.The calibration and identification performance of the risk prediction model for intraoperative hypothermia in thoracoscopic surgery patients constructed in this study are strong,which can provide assistance for effective prediction and assessment of the risk of intraoperative hypothermia in patients in the early stage.The risk prediction model is presented in the form of a column chart,which is easy to operate and more suitable for clinical application.Although the model has not been externally validated,it still has certain reference value.